Gaussian Process Approximate Dynamic Programming for Energy-Optimal Supervisory Control of Parallel Hybrid Electric Vehicles.
Jin Woo BaeKwang-Ki K. KimPublished in: IEEE Trans. Veh. Technol. (2022)
Keyphrases
- gaussian process
- approximate dynamic programming
- electric vehicles
- power grid
- dynamic programming
- linear program
- regression model
- control policy
- reinforcement learning
- semi supervised
- average cost
- bayesian framework
- model selection
- latent variables
- markov decision processes
- real time
- policy iteration
- power system
- energy consumption
- long run
- evolutionary algorithm
- optimal solution